Evolution and driving mechanisms of high-speed railway network structure in urban agglomerations from a multi-dimensional resilience perspective: An analysis based on complex network and tergm models

With the rapid expansion of China’s high-speed railway (HSR) network, the stability and recovery capacity of the system under multiple disturbances have become key issues in the governance of urban agglomeration transportation. Taking China’s HSR networks as the research object, this study establishes a complex network model and selects four indicators—Matchability, Transitivity, Hierarchy, and Aggregation—to describe the network’s static resilience, dynamic resilience, and comprehensive resilience. It further investigates the spatiotemporal evolution characteristics and driving mechanisms of network resilience from 2015 to 2024. The results show that:(1) Static resilience presents a trend of initial growth followed by stabilization. The network structure maintains a “core–periphery” pattern, spatial heterogeneity gradually decreases, and both aggregation and redundancy are significantly enhanced, continuously improving system robustness. (2) Dynamic resilience shows an upward trend under both random and deliberate attack simulations, indicating that the network’s adaptability and recovery ability under disturbances are continuously strengthened, and the impact of core-node failures on overall performance is gradually reduced. (3) Comprehensive resilience demonstrates a phased evolution from “structural expansion–functional optimization–synergistic stabilization,” implying a transformation of the HSR network from scale-driven growth to coordinated structural–functional development. (4) Driving mechanism analysis reveals that reciprocity, transitivity, government investment, and living standards have significant positive effects on the formation and evolution of network resilience, while economic development exerts a negative inhibitory effect. The findings reveal the evolutionary path of the HSR network from quantitative expansion to qualitative optimization and provide theoretical and practical references for structural optimization and resilience enhancement of urban agglomeration transportation systems.